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<p>In mass customization, evolving trends demand a flexible production structure and a reconfigurable manufacturing system to support a variety of product categories and smart logistics. These trends generally necessitate a flexible production environment to accommodate a wide variety of products under uncertain demands by implementing a reconfigurable manufacturing system. This research introduces a digital twin emulator (DTE) driven design framework for production lines and proposes a method to optimize a reconfigurable production line in a smart factory setting. The proposed method adopts a multi-objective optimization (MOO) approach in simulating of the alternative reconfigurable production lines. The optimization problem of production scheduling in a reconfigurable production line is identified to develop a mathematical model based on engineering design parameters and modular configurations. Subsequently, a DTE model is utilized to optimize the production line with three objectives, such as minimizing production costs, reducing production time, and enhancing production balance rate. A genetic algorithm is applied to determine an optimal production schedule in the production lines. Results from a case study show that the proposed method effectively enhances the reconfigurability of the production line and improves overall production performance in a smart logistics and factory environment.</p>

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Simulation-Based Decision-Making for Reconfigurable Production Line Design and Optimization with a Digital Twin Emulator

  • 期刊论文

  • 发表日期：

    2025年6月2日

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  • Pengcheng Wang,
  • Jongsuk Lee,
  • Guo Sheng Lee,
  • Seung Ki Moon,
  • Manuel Lopez

摘要

In mass customization, evolving trends demand a flexible production structure and a reconfigurable manufacturing system to support a variety of product categories and smart logistics. These trends generally necessitate a flexible production environment to accommodate a wide variety of products under uncertain demands by implementing a reconfigurable manufacturing system. This research introduces a digital twin emulator (DTE) driven design framework for production lines and proposes a method to optimize a reconfigurable production line in a smart factory setting. The proposed method adopts a multi-objective optimization (MOO) approach in simulating of the alternative reconfigurable production lines. The optimization problem of production scheduling in a reconfigurable production line is identified to develop a mathematical model based on engineering design parameters and modular configurations. Subsequently, a DTE model is utilized to optimize the production line with three objectives, such as minimizing production costs, reducing production time, and enhancing production balance rate. A genetic algorithm is applied to determine an optimal production schedule in the production lines. Results from a case study show that the proposed method effectively enhances the reconfigurability of the production line and improves overall production performance in a smart logistics and factory environment.